Authors: Shree Harsh Attri; T.V. Prasad; Gavirneni RamaKrishna
Addresses: Department of Computer Science and Engineering, JIMS Engineering Management Technical Campus, 48/4, Knowledge Park III, Greater Noida, Knowledge Park III, Noida, Uttar Pradesh 201303, India ' GIET Institutions, NH-16, Chaitanya Knowledge City, Rajahmundry, Andhra Pradesh 533296, India ' Department of Computer Science and Engineering, KL University, Green Fields, Vaddeswaram, Andhra Pradesh 522502, India
Abstract: The demand of bilingual code switching has significantly increased due to cross-lingual communication and information exchange at a global scale and specifically in India. The core component of MT system is identification and translation of morphological inflections and PoS word ordering with respect to language structure. Indian languages are morphologically richer than English language and have multiple inflections during translation into English language. This paper focuses on the analysis and translation of code mixed language, i.e., Hinglish into pure Hindi and pure English languages. The experiments based on the algorithms in the paper are able to translate code mixed sentences to pure Hindi with a maximum success rate of 91% and to pure English with a maximum success rate of 84%.
Keywords: verb follower connotations; pronoun modulations; bilingual nouns; gender modulations; gender specific suffix; adjective modulations; natural language processing; bilingual NLP.
International Journal of Cloud Computing, 2021 Vol.10 No.4, pp.278 - 298
Received: 12 Sep 2019
Accepted: 23 Dec 2019
Published online: 29 Nov 2021 *